• DocumentCode
    2596539
  • Title

    Shape representation and recognition from curvature

  • Author

    Dudek, Gregory ; Tsotsos, John K.

  • Author_Institution
    Res. Centre for Intelligent Machines, McGill Univ., Montreal, Que., Canada
  • fYear
    1991
  • fDate
    3-6 Jun 1991
  • Firstpage
    35
  • Lastpage
    41
  • Abstract
    An approach for describing objects for the purpose of recognition is developed. The authors deal with two key issues: building natural descriptions of curved objects, and making these descriptions compact and abstract. Typical examples of the types of curve one is able to describe as both qualitatively similar, yet discriminably different, are shown. Methods based on curvature extrema alone are likely to find three of the four of these shapes indistinguishable, while methods based on approaches such as shape templates may be oblivious to their similarity. The central ideas of the approach are outlined
  • Keywords
    computer vision; computerised pattern recognition; curvature extrema; curved objects; natural descriptions; shape recognition; shape representation; shape templates; Art; Data mining; Dynamic programming; Interpolation; Noise measurement; Noise shaping; Robustness; Shape; Smoothing methods; Target recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2148-6
  • Type

    conf

  • DOI
    10.1109/CVPR.1991.139657
  • Filename
    139657